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252 DU Journal of Undergraduate Research and Innovation Developing a Connect between Spiritual Ecology and Sustainability in theUniversity Curriculum through an Empirical Study Pratibha Rai, Prem Kumari Srivastava and Saumya Shukla [email protected], [email protected], [email protected] Maharaja Agrasen College, Cluster Innovation Centre, Maharaja Agrasen College University of Delhi ABSTRACT With baseline identification works of scholars and practitioners such asBerry (2009),Vaughan Lee(2013),Rockefeller & Elder (1992), Kinsley (1995) and Wangari (2010)who argue that the global environmental dilemma is a consequence of a spiritual and moral predicament resulting from a lack of connectedness to, or alienation from, the other than humannatural world, the paper builds the connect between spiritual ecological consciousness and responsible ecological behaviour. The present comparative research presents findings on two educational knowledge systems of India: the University of Delhi (DU), and Dayalbagh Educational Institute (DEI) (Deemed University) Agra. The basis of this comparative study is the use of a General Ecological Behaviour (GEB) Scale (Kaiser et al 1999) slightly modified as a tool to assess the ecological conduct of groups forming: a student community exposed to modern education system with regular exposure to spiritual ecological practice vis a vis a community exposed to modern education system without spiritual ecological practice.. The researchers believe that the concept of spiritual ecology if ingrained deeply is likely to convert into ecological behaviour that fosters development on the planet Earth that is sustainable, respecting claims of the posterity. The interesting empirical findings of the study support the hypothesis and the results indicate comprehensive theorising. The Spiritual ecological consciousness level as a determinant of Ecological behavior Intent is stronger in the DEI data vis-a-vis DU data but the effect is small in both the data sets. The spiritual ecological awareness is there amongst the students but the conversion/transformation of this awareness to consciousness level is required at deeper level amongst both the student communities and this might happen with age and with continuous practice. The results are suggestive of creating a spiritual ecology centric education system that emboldens the progress towards sustainable development. Keywords: ecological behavior intent (ebi), environmental responsibility(er), environmental knowledge(ek), general ecological behaviour(geb), spiritual ecological consciousness (sec), Volume 1 Issue 2, Page 252-274
Transcript
Page 1: Developing a Connect between Spiritual Ecology and ...journals.du.ac.in/ugresearch/pdf/Pratibha 16.pdfDeveloping a Connect between Spiritual Ecology and Sustainability in theUniversity

252

DU Journal of Undergraduate Research and Innovation

Developing a Connect between Spiritual

Ecology and Sustainability in theUniversity

Curriculum through an Empirical Study Pratibha Rai, Prem Kumari Srivastava and Saumya Shukla

[email protected], [email protected], [email protected]

Maharaja Agrasen College, Cluster Innovation Centre, Maharaja Agrasen College

University of Delhi

ABSTRACT

With baseline identification works of scholars and practitioners such asBerry (2009),Vaughan

Lee(2013),Rockefeller & Elder (1992), Kinsley (1995) and Wangari (2010)who argue that the

global environmental dilemma is a consequence of a spiritual and moral predicament resulting

from a lack of connectedness to, or alienation from, „the other than human‟ natural world, the

paper builds the connect between spiritual ecological consciousness and responsible ecological

behaviour. The present comparative research presents findings on two educational knowledge

systems of India: the University of Delhi (DU), and Dayalbagh Educational Institute (DEI)

(Deemed University) Agra. The basis of this comparative study is the use of a General

Ecological Behaviour (GEB) Scale (Kaiser et al 1999) slightly modified as a tool to assess the

ecological conduct of groups forming: a student community exposed to modern education

system with regular exposure to spiritual ecological practice vis a vis a community exposed to

modern education system without spiritual ecological practice.. The researchers believe that the

concept of spiritual ecology if ingrained deeply is likely to convert into ecological behaviour

that fosters development on the planet Earth that is sustainable, respecting claims of the

posterity. The interesting empirical findings of the study support the hypothesis and the results

indicate comprehensive theorising. The Spiritual ecological consciousness level as a

determinant of Ecological behavior Intent is stronger in the DEI data vis-a-vis DU data but the

effect is small in both the data sets. The spiritual ecological awareness is there amongst the

students but the conversion/transformation of this awareness to consciousness level is required

at deeper level amongst both the student communities and this might happen with age and with

continuous practice. The results are suggestive of creating a spiritual ecology centric education

system that emboldens the progress towards sustainable development.

Keywords: ecological behavior intent (ebi), environmental responsibility(er), environmental

knowledge(ek), general ecological behaviour(geb), spiritual ecological consciousness (sec),

Volume 1 Issue 2, Page 252-274

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INTRODUCTION

The human spirit as an amalgam of energies, both mental and physical can recreate a

sustainable world and reverse the path of development, which is destructive and vicious. (Lee,

2013) Ecological sustainability depends upon spiritual wakefulness and an attitude of

conscientiousness. It has been recognised by spiritual ecologists that the creation is sacred and

this sacredness should be venerated by our behavior. (Macy, 2012). In the wake of growing

environmental problems like global warming, extinction of species and overconsumption, we

human beings have to change our underlying attitudes and beliefs about the earth, and our

spiritual responsibilities towards the planet. The present study was initiated with the belief that

the more we expand the self to identify with “others”(people, animals, ecosystems) the more

we realize ourselves. (Fox,1990)

Fox (1990) has used transpersonal psychology to validate this thought. An increasing dominant

mechanical and global perspective and an insatiable need for material goods and technological

development severed the collective sense of sacredness. There is no concurrence between

anthropocentric environmentalism, which deals with environmental conservation specifically

for exploitation for and by human beings and spiritual ecology. An integrated path is taken by

spiritual ecology where it recognizes that all the different components of the ecosystem

together with human beings function as a unit. (Lee. 2013) This underlying philosophy has

ushered an entirely new set of environmental ethics, which promotes simple living, population

control, and preservation of wilderness and the Green movement.

The key contribution in this study is two-fold. First, we make a theoretical contribution by

presenting an integrative and comprehensive viewpoint about the relationship that exists

between spiritual ecological consciousness and general ecological behavior. Second, we also

make two methodological contributions. One, we modify environmental value scale (Kaiser et

al.1999) to a spiritual ecological consciousness scale. This as per eastern philosophy is a more

encompassing concept determining the ecological behavior via environmental responsibility…

Positive ecological behaviour often gets reinforced with higher level of spiritual ecological

consciousness identifying oneself with the whole and overall behavior of an individual in

general. Two, none of the studies has attempted to quantify the relationship between spiritual

ecological consciousness and general ecological behavior in the Indian context till now. A

modest attempt has been made in this study to enumerate the various indicator variables that

should be included in the spiritual ecological consciousness scale. The major difference in the

approach of this study is the novelty in conceptualization. We empirically tested and validated

our proposed framework using component-based Partial Least Square (CB-PLS) path-modeling

technique using cross section data collected from the student community following slightly

distinct education systems. We begin by developing hypotheses that offer a conceptual

framework for examining the impact of value based education system in spirit and in practice

on general ecological behavior. The methodology will be discussed in the subsequent section

followed by data analysis. The interpretation of the findings is discussed in the next section.

Discussion, conclusion and recommendations are finally presented towards the end.

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THEORY AND HYPOTHESES DEVELOPMENT

The deep-rooted spiritual intelligence shapes up the sustainability theory which enunciates that

a distinct spiritual unity manifests in all life forms leading to spiritual growth. (Korten, 2013).

Over centuries the Asian cultures have imbibed the values of community living and spirituality.

Indigenous Asian societies have retained these values as individual interests being subservient

to larger interests of the community and nature. This insight has resulted in innumerable socio-

cultural practices like planting two trees when one is cut; giving nature time to heal and

replenish the resource. Whenever dissipation of natural resource was an outcome of

technological advancement for human comfort, Asians have given time to bring the resource to

regenerative level. Asian cultural practices sustainability principles embedded in them.

In Asian communities, an individual‟s existence and functionality is dependent on symbiotic

and harmonious living relationship with the whole environment. The recognition of strong

linkages with ecosystems of the natural habitat amongst the communities awakened a sense of

societal spiritual unison. (Kurten, 2013). These communities have a tendency to nurture the

cultural values that recognize a linkage between the needs of the present generations and the

posterity. Personal advancement on the spiritual course moulds the directional preferences in

life. Seeking personal fulfilment via material possessions takes a back seat. The search for

mental peace takes man closer to actions that lead to sustainable living. (Rajvanshi, 2010)

Reinforcing the significance of a symbiotic relationship between humans and their

environment, both living and non- living, and the importance of fostering environmental

sustainability through responsible ecological behaviour is well recognised fact. In pursuance of

the above fact we endeavour to identify the spiritual values that are responsible for positive

ecological behaviour. This requires understanding the concept of spiritual ecology and its

impact on human behaviour. With this ideological faith, our team initiated the project of

quantifying a connect between spiritual ecological awareness/consciousness level (combination

of spiritual values and environmental values) and ecological behavior of two student

communities, those of Dayalbagh Educational Institute and the University of Delhi exposed to

different educational systems . The premise of the study is based on following hypotheses.

Hypotheses:

Hypothesis 1:

Environmental knowledge shapes Ecological Behaviour Intent.

Hypothesis 2:

Environmental responsibility reinforces Ecological Behaviour intent.

Hypothesis 3.Spiritual ecological consciousness strengthens

(

a) the environmental responsibility.

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(b) and hence works through ecological behaviour intent and reflects in conduct of ecological

behaviour.

Hypothesis4: Ecological Behaviour Intent jointly determined by environmental knowledge,

environmental responsibility and spiritual ecological consciousness determines the General

ecological behaviour that is reflected through four sub constructs: Garbage Reduction,

Conservation of power and water, Ecological vehicle use and Nature protection activities. In

accordance with this hypothesis, the scales were adapted to measure all constructs.

CONCEPTUAL FRAMEWORK

Structural Model:

We adapted and modified the first order constructs as reflective measurement models from

Kaiser et al studies (1999, 2000) in the Indian context. We also intuitively felt that believing in

oneness of the universe strengthens the compassion for nature hence we took spiritual

ecological consciousness instead of environmental value as one of the endogenous reflective

construct, the other construct is environmental knowledge that determines the ecological

behaviour of an individual via the intermediating reflective construct the ecological behavior

intent. The measurement model constituted four first order explanatory reflective (predictor)

constructs: i) environmental knowledge; ii) environmental responsibility; iii) spiritual

ecological consciousness; iv) ecological behavior intent and general ecological behaviour as a

reflective explained construct comprising of four second order sub constructs :a) garbage

reduction; b) conservation of power and water ; c) nature protection activities; d) ecological

vehicle use. In this case, the first-order constructs are dependent variables and the second- order

factors becomes the independent variable (Byrne,2001).

Ecological

Behaviour Intent

General Ecological

Behaviour

Garbage

Reduction

Conservation of

water & Power

Nature Protection

Activity

Ecological

Automobile Use

Environmental

Knowledge

Environmental

Responsibility

Spiritual

Ecological

Conciousness

H1

H2 H4

H3a

H3b

Ecological behaviour is a function of environmental knowledge, spiritual ecological

consciousness, ecological behaviour intent and environmental responsibility. (adapted from

Kaiser et.al study 1999)

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Measures

Using this research design, we assessed the validity of the content from the preliminary group

of items generated from earlier studies of experts in this domain. In line with the concept and

definition of spiritual ecology that emphasizes ecosystems as a constituent of different

components functioning as a complete unit, initially 20 items were selected as determinants of

spiritual ecological consciousness were selected. (The opinion of experts were sought to

determine the sufficiency of every item by ranking the degree and whether it was able to

measure the construct effectively on a 5-point Likert type scale(Rai, 2013). A ranking of 1

suggested a very low adequacy, and a ranking of 5 suggested an extremely high level of

adequacy. The mean adequacy score for every item was calculated as the average marks given

by the respondents. The standard deviation of adequacy score was then computed.(Rai, 2013)If

the mean adequacy score was found to be more than 3 and the standard deviation was less than

1, the item was retained. 12 items were deleted, 3 items were modified and 2 items were added

after reviews conducted by the experts in pretest.

Scale purification was done along with examination of scale‟s dimensionality and reliability.

10 items were retained in the spiritual ecology scale. There were 5 items representing

environmental value and 5 items for spiritual consciousness that were picked up from extant

literature review (Underwood &Teresi 2002 ; Lee, 2010), 5-point Likert-type scales were used

to capture spiritual ecological consciousness varying from strongly agree to strongly

disagree, regarding different facets of spiritual ecology.

It was appropriate to use the 5-point scale anchor since it would have been difficult for

respondents to differentiate the response points given in the scale which would, otherwise,

dilute the response validity (Clark & Watson, 1995). Reduction in the response options could

have resulted in making the informants choose a neutral response by opting for the scale

midpoint (Prendergast & Huang, 2003).

We used multi-item scales for dependent and explanatory variables, with each item measured

using a 5-point Likert type scale, where a score of 1 indicated very strongly disagree, while a

score of 5 indicated very strongly agree. We followed Kaiser et al (1999,2000,2003) to

generate the initial items for the study constructs with slight adaptation. We studied the usable

cases, (i) one for assessing dimensionality, validity and reliability and of the measures for all

the individual constructs; and (ii) for testing the hypothesized conceptual model.

Dependent variable

General Ecological Behavior comprising of four sub constructs a) effort towards garbage

reduction and removal; b) attempt to conserve power and water; c) Volunteering in nature-

protection activities; (Kaiser. 1998) d) Ecological vehicle use

Explanatory variables

1. Spiritual Ecological Consciousness 2. Environmental Knowledge 3. Environmental

Behaviour Intent

4. Environmental responsibility

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Data Collection Strategy

We developed the survey and collected the data for this study in three stages: (i) qualitative

field interviews (ii) pre-test and (iii) survey administration.

Qualitative field interviews

We conducted 10 explorative interviews with four academic researchers involved in the study

of ecology and 3 spiritual practitioners. Each interview lasted between 60 and 90 minutes. We

also conducted a detailed literature review to identify the necessary scale items to measure

(Schilke & Goerzen, 2010)various constructs of this study.

Pre-test

We contacted 20 students for the pre-test of the survey out of which 12 agreed to participate in

the pre-test of the survey. After completing the pre-test, we conducted interviews with them.

Based on their feedback, we finalized the format of the survey and the guidelines for the

respondents.

Sample and data collection

The study population comprised of student community of metro cities mainly from Delhi

University and from Dayalbagh Educational Institute (Deemed University) Agra. We collected

the data from May 2013 to October 2013 by using the websites of survey monkey.com and

googledrive.com. We used questionnaire method as a survey instrument. The instrument briefly

introduced the informants to the objectives of the study and had a no objection clause

pertaining to use of information provided by the respondent for research purpose was added in

the questionnaire. We disseminated the survey to 2500 students. We received 558 responses

out of which 451 surveys were usable, reflecting a response rate of 22.32 percent. Table 1

reflects characteristics of the sample.

Table 1

Characteristics of the Sample

Respondent

characteristics

Delhi

University

Dayalbagh

Educational

Institute

N = 256 N = 195

Gender of

Respondents

Male 48% 62%

Female

Age of the

respondents (yrs.)

18-21 42% 78%

22-25 58% 22%

Type of Upbringing

Urban 60% 42%

Semi-urban 22% 35%

Rural 18% 27%

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Exposure to Value

Based Education

80% 54%

ANALYSIS AND RESULTS

Data purification

We adopted the univariate approach (Hair et al.,1998) to identify outliers. As the size of the

sample was more than 80, we used the criteria of -4-≤ Z ≤ 4 to determine the outliers (Hair et

al., 1998). As per the results, there were no significant outliers. Following Newman (2003),

we did not include completed questionnaires which had more than 10% missing values, and

imputed the less than 10% missing values using Maximum Likelihood (ML) estimation.

Following Armstrong and Overton‟s (1977) approach, we examined the non-response bias

among the informants by comparing early respondents with late respondents.(Rai, 2013).

Reminder e-mails were sent to non-respondents after waiting for three weeks for their response

as this period of three weeks was used as a cut-off time period for response between late and

early respondents. We assumed that there is no difference between late and early respondents,

and the t-tests results indicated absence of considerable differences in the average of all items

between the early and late respondents (p > 0.05).(Lew& Sinkovics, 2013).

We also assessed the data to examine linearity, multivariate normality, heteroscedasticity,

multicollinearity, and autocorrelation. The data was not normally distributed as reflected by

Shapiro Wilk test (p<.05)(Shapiro & Wilk,1965).We analyzed the validity and internal

consistency of the indicator variables by carrying out exploratory factor. Item pool selected

based on factor loadings is given in Table2.

Table 2

Table 2

Item Pool used in different constructs after Pretest along with the source

Latent construct 1: Spiritual ecological consciousness Factor

loading

Cronbach

alpha

SEC1 There is some Higher Power/Universal intelligence. .729

.857

Underwood L.G.

&Teresi J, 2002 SEC2 I experience a spiritual dimension that gives me strength and

love, and gives meaning to life.

.784

SEC3 Spiritual thoughts, meditation and prayer connects me with nature.

.749

SEC4 I am a part of the Earth, not separate from it. My faith

strengthens the belief of interconnectedness that exists amongst

all components of the universe.

.689 Llewellyn

Vaughan Lee,

2010

SEC5 All living and non living things have the right to exist. All

organisms‟ lives are precious and worth preserving.

.653 Underwood L.G.

& J. Teresi 2002

SEC6 Nature must be preserved as supernatural force and God are an

integral part of it.

.671

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SEC7

I am liable for all my actions that include affecting the

environment to a Supreme force.

.761 Llewellyn

Vaughan Lee,

2010

Latent construct 2: Environmental knowledge

.780

Florian G Kaiser,

et.al 1999

EK1 All living beings have a symbiotic relationship. .741

EK2 Human actions brings poisonous metals in our food chain

through pollution of ground water, use of pesticides etc.,

.768

EK3 Presence of Ozone close to ground level may cause respiration

problems.

.701

EK4 The excessive and continuous release of CO2 will greatly

change the climate of the world.

.686

EK5 There will be interruption in the food chain due to extinction of

many species and this will affect many species in the

subsequent food chain cycle

.703

Latent construct 3: Environmental Responsibility

ER1 My personal contribution is very small, I don‟t feel responsible

for air pollution

.605 Florian G Kaiser

et.al 1999

ER2 I drive an automobile, I contribute to and I‟m responsible for

air pollution.

.612 .603

ER3 I feel party to the creation of the present environmental

problems.

.566

ER4 I feel individual contribution towards environmental

conservation will go a long way in reducing the damages being

done to the environment.

.490 Added in Indian

context

Intermediating Latent construct 4: Environmental Behaviour Intent

.751

Florian G Kaiser,

et.al 1999

EBI1 I will endeavour and support to make the inner cities free from

automobile.

.598

EBI2 I would prefer not to drive to work any longer. .820

EBI3 My preference would be to go shopping without using my

personal vehicle.

.831

EBI4 My preference would be to use my personal vehicle only when

there is no other transportation mode available.

.761

Endogenous Latent Construct 5: General Ecological Behaviour- 4 sub

constructs

Sub construct : Garbage Reduction

.731

GR1 I ensure, used paper & news-paper isn‟t wasted & is sold for

recycling or reuse.

.677 F.G. Kaiser & A

Biel, 2000

GR2 I prefer paper and cloth bags to plastic bags for shopping. .869

GR3 I try to minimise use of plastics and plastic bags.

.879 adapted in Indian

context

Sub construct: Conservation of Power & Water .684

CPW1 I prefer to fill the bucket and then take bath instead of using the

shower.

.699 F.G. Kaiser & A

Biel, 2000

CPW2 If clothes are hand washed, tap water is not kept running till

the entire process is completed.

.791 adapted in Indian

context

CPW3 I ensure, while cleaning utensils tap water is not wasted by

domestic help or by me.

.842

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Sub construct: Nature protection activity

.694 NPA1 I actively participate in conservation drives of environmental

groups

.853 F.G. Kaiser & A

Biel, 2000

NPA2 In past, I’ve politely pointed out to people their un-ecological

behaviour.

.766

NPA3 I contribute financially to environmental organisations. .742

Sub construct: Ecological automobile use

.761

EVU1 I usually drive, in terms of speed, to minimise my fuel

consumption.

.728 adapted in Indian

context

EVU2 I prefer to switch off the engine of the vehicle at traffic red

lights, traffic jams or while waiting for someone.

.800

EVU3 I walk or take public transport whenever possible.

.786 F.G. Kaiser & A

Biel, 2000

EVU4 I recommend owning a fuel efficient car.

.737 adapted in Indian

context SEC =spiritual ecological consciousness, EK=environmental knowledge, ER=environmental responsibility, EBI=Environmental behavior intent,

GR= Garbage reduction, CPW=Conservation of power and water , NPA= Nature protection activity, EVU=Ecological automobile use

Common Method Bias

As we had collected all the measurement items through the uniform survey instrument, this has

increased the possibility of common method bias (CMB) (Podsakoffet al., 2003). Post-hoc

analysis was conducted by using two statistical methods. First, we conducted one-factor test of

Harmon (Podsakoff and Organ, 1986). The un-rotated factor solution results indicated that the

extracted factor could explain only 31.87% (<50%) of the variance. As there was no single

dominant factor, we assumed that CMB did not affect the significance of the relationships.

(Rai, 2013).Second, we conducted the common latent factor method (Williams and Anderson,

1994), a more robust test, by adding a latent factor to the confirmatory factor analysis (CFA)

model, connecting it to all observed items in the model, and then constraining the regression

coefficients of the paths from this common latent factor to all the observed variables as equal.

The unstandardized regression weights from the common latent factor was found to be

approximately 0.14 and when squared, these unstandardized regression weights from the

common factor was found to be about 1.96%, which is the common shared variance, suggesting

that there was no problem of CMB in the data. (Rai, 2013)

Scale Validity and Reliability

In this study, we hence considered each and every first-order constructs as reflective

measurement models. We analyzed the validity and internal consistency of the first-order

constructs in two stages. First, we assessed the unidimensionality of these constructs by

carrying out exploratory factor analysis (EFA). There is no universally accepted cut-off value

for loadings, but we considered a loading of more than 0.4 (all values ≥ 0.56) for every

construct as a good measure of their latent i.e. hidden construct. The results of the EFA

confirmed the unidimensionality. Next, we examined the internal consistency by calculating the

Cronbach‟s alpha for each first-order construct.

Table 3 shows that Cronbach‟s alpha for the items within each construct is more than the

threshold assessment value of 0.6 (all are ≥ 0.69) (Nunnally, 1978), providing evidence of

internal reliability.(Table2)

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Convergent Validity and Discriminant Validity

The convergent validity of constructs of the first order were assessed by adopting three

criterion.(Johnnes et al. 2012)First, the confirmatory factor analysis (CFA) results demonstrate

that for each first- order constructs model of measurement, the fit indices were within the

acceptable limits and the items factor loadings were found to be above the threshold limit of

0.4 (all were ≥ 0.52) (Table 2) (DeVellis, 2003).

Second, the composite reliability of all the first order constructs is above 0.60 level (all were ≥

0.77) (Bagozziet al., 1991). Third, we carefully analysed the average variance extracted (AVE).

The shared variances as depicted in Table 3 gives clear indication that these are higher than the

suggested level of threshold (all were ≥ 0.52),thus supporting the convergent validity of the

first-order scales.(Hair et al.,2012;Fornell and Larcker,1981)

We assessed the discriminant validity using Fornell and Larcker‟s (1981) criterion, which

requires that thesquare of largest correlation between two constructs should be smaller than the

AVE of the construct. All along the length of the diagonal, AVE for every construct is shown

in Table 4.

Also the square of correlation coefficients that exists between all linked constructs in theory

appear as elements in the off-diagonal. (Cameron, 2004) When off- diagonal elements as

appearing in matching columns and rows are found to be less than the diagonal element, the

construct‟s discriminant validity is stated to be adequate.

Table 3 shows that this criterion is satisfied. The evidence of all constructs discriminant

validity has been provided by the stated tests. The existence of discriminant validity amongst

the constructs is indicated by the results of cross loadings since an indicator‟s loadings on its

own construct are in all cases higher than all of its cross loadings with other constructs

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Table3

DEI Sample Convergent Validity

R2 C.A AVE CR R

cpw 0.4092 0.6012 0.5613 0.7907 0.228

evu 0.5785 0.7609 0.5823 0.8476 0.3397

ebi 0.212 0.7289 0.5507 0.8301 0.0371

ek 0 0.8478 0.684 0.8814 0

er 0.1941 0.6979 0.6727 0.7196 0.0433

geb 0.1832 0.0433 0.6900 0.8164 0.0582

gr 0.6445 0.7361 0.6598 0.8519 0.424

npa 0.5392 0.6934 0.6172 0.8273 0.3246

sec 0 0.8563 0.5367 0.8899 0

DU Sample Convergent Validity

R2 CA AVE CR R

cpw 0.4725 0.5714 0.5675 0.7435 0.1673

evu 0.3996 0.5245 0.6064 0.7265 0.1581

ebi 0.1419 0.6269 0.5723 0.7808 0.0576

ek 0 0.7775 0.6961 0.8332 0

er 0.2532 0.4234 0.7191 0.7298 0.0549

geb 0.1483 0.7162 0.5178 0.7907 0.0317

gr 0.4437 0.5563 0.6303 0.7488 0.1874

npa 0.6191 0.5577 0.5306 0.7710 0.3273

sec 0 0.6476 0.6010 0.7627 0

R2 = R Square, C.A.= Cronbach Alpha, AVE = Average Variance Extracted, CR= Composite Reliability, R= Redundancy

*cpw=conservation of power and water , evu=ecological vehicle use, ebi =environmental behavior intent,

ek =environmental knowledge, er =environmental responsibility, geb=general ecological behavior,

gr= garbage reduction, , npa= nature protection activity, sec =spiritual ecological consciousness.

Table 4

_______________________________________________________________________________

Discriminant Validity of DU sample using Fornell- Larcker Condition

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cpw evu ebi ek er geb gr npa sec

cpw 0.5613

evu 0.0836 0.5823

ebi 0.151 0.0522 0.5507

ek 0.0635 0.0471 0.1083 0.684

er 0.0674 0.0335 0.1197 0.2783 0.6727

geb 0.4092 0.2121 0.1822 0.1128 0.1269 .69 00

gr 0.1814 0.1984 0.0798 0.0705 0.1042 0.3633 0.6598

npa 0.1022 0.1604 0.1577 0.0721 0.0528 0.5391 0.2106 0.6172

sec 0.1038 0.173 0.114 0.1338 0.094 0.1163 0.0726 0.1005 0.5367

Discriminant validity of DEI sample using Fornell- Larcker condition

cpw evu ebi ek er geb gr npa sec

cpw 0.5675

evu 0.1925 0.6064

ebi 0.0383 0.079 0.5723

ek 0.0222 0.0335 0.1363 0.6961

er 0.0123 0.0368 0.0275 0.0969 0.7191

geb 0.4725 0.3995 0.1483 0.0196 0.1423 0.5178

gr 0.019 0.0588 0.0745 0.0025 0.0692 0.4436 0.6303

npa 0.1158 0.1058 0.0985 0.0021 0.0886 0.6192 0.207 0.5306

sec 0.0076 0.0452 0.0118 0.1574 0.1832 0.0179 0.0772 0.0089 0.601

*cpw=conservation of power and water, evu=ecological vehicle use, ebi =environmental behavior intent,

ek =environmental knowledge, er =environmental responsibility, geb=general ecological behavior,

gr= garbage reduction, npa= nature protection activity, sec =spiritual ecological consciousness.

These results emphasize the reliability, convergent and discriminant validity of the

measurement models (Schilke & Goerzen 2010) of all the first-order constructs.

Validity of Second-order Constructs

Since we had conceptualized general ecological behavior as a reflective-reflective type four-

dimensional second-order construct, hence we also examined the validity and strength of these

constructs. Factor loadings of the first-order latent constructs on the second-order construct

were greater than 0.4 (all values are ≥ 0.56) (Table 2), thus indicating that each first-order

construct was a good measure of its latent construct. We also assessed the convergent and

discriminant validity of these second-order constructs. Table 2 shows that the CR of all the

second-order constructs is above 0.7 levels. The AVE for each second-order construct is above

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0.5.The AVE coupled with the strengths and significances of the parameter estimates of each of

the reflective scales provides evidence of convergent and discriminant validity of the second-

order constructs. The magnitude of the parameter estimates and the significance along with

high AVE of each of the reflective scales gives verification that the second order constructs

have convergent and discriminant validity.

Owing to different logic of measurement, one cannot apply the set criterion for evaluating

reflective constructs, given as internal consistency and convergent validity, to assess formative

measurement models (Diamantopoulos & Siguaw, 2006).Hence, we tracked the

recommendations of Henseler et al.(2009) and Hair et al.(2012) and employed

multicollinearity criterion and outer weights to examine the measurement features of the

formative second order construct (Diamantopoulos & Winklhofer,2001; Bollen& Lennox,

1991). The variance inflation factors (VIF) were found to be much below the permissible level

of 5 as the basis for test of multicollinearity (Hair et al., 2012). In addition, all item‟s weights

were found to be significant(p<.001) (Cenfetelli &Bassellier, 2009). The correlation (Table 5)

between the constructs indicate that the constructs are independent of each other and suitable to

examine further to assess relationships amidst them.

Table 5

__________________________________________________________________________________

Correlation matrix of latent variables :DU sample

cpw evu ebi ek er geb gr npa sec

cpw

evu 0.2892

ebi 0.3886 0.2285

ek 0.252 0.2172 0.3291

er 0.2598 0.1831 0.346 0.5276

geb 0.6397 0.4606 0.4269 0.336 0.3563

gr 0.426 0.4455 0.2825 0.2657 0.3229 0.6028

npa 0.3197 0.4006 0.3972 0.2687 0.2998 0.7343 0.459

sec 0.3222 0.1317 0.3778 0.3659 0.3067 0.3411 0.2695 0.3216

correlation matrix of latent variables :DEI sample

cpw evu ebi ek er geb gr npa sec

cpw

evu 0.4388

ebi 0.1959 0.2812

ek 0.1493 0.1833 0.3692

er 0.111 0.1919 0.166 0.3114

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geb 0.6874 0.6321 0.3851 0.14 0.3773

gr 0.1379 0.2426 0.273 0.0504 0.2631 0.6661

npa 0.3404 0.3254 0.3139 0.0464 0.2977 0.7869 0.455

sec 0.0876 0.2128 0.1088 0.3698 0.4281 0.1339 0.278 0.0945

________________________________________________________________________________

*cpw=conservation of power and water , evu=ecological vehicle use, ebi =environmental behavior intent,

ek =environmental knowledge, er =environmental responsibility, geb=general ecological behavior,

gr= garbage reduction, , npa= nature protection activity, sec =spiritual ecological consciousness.

The Model‟s Predictive Strength

We analyzed the model‟s predictive strength by using R2statistics of the general Ecological

behavior, which is the only endogenous construct in the model.(Lew& Sinkovics, 2013)The R2

value is 0.183 for the DU sample and .148 for the DEI sample which is more than the

permissible threshold of 0.1 (Falk & Miller, 1981).R2 statistic of intermediating construct of

environmental responsibility and environmental behavior intent in the Delhi University sample

(.19 and 21) and the Dayalbagh Educational institute sample (.14, and 25) is also found to be

higher than the threshold limit. Therefore, there is substantiation of the appropriateness of

conceptual model for measuring the General Ecological Behaviour, that is, the conceptual

model explains significant proportion of the squared standard deviation in endogenous

construct.

We evaluated the predictive weight of the conceptual model by means of Stone-Geisser‟s Q2

statistic (Stone, 1974; Geisser, 1975; Lew& Sinkovics 2013). We used blindfolding re-

sampling approach to compute the Q2

statistic. The Q2 values for the endogenous construct

GEB was greater than zero (0.22, .19) for both DEI and DU sample substantiating the

predictive significance of the model (Chin, 1998).

Test of hypotheses

Testing of hypotheses was done by assessing the sign and measure of structural path

coefficients and the corresponding t-values, measured by applying nonparametric bootstrapping

technique (Chin, 1998).

Effect size

To assess the strength of the main effects and interaction effects, the effect size f2were

calculated using the formula: f2= (R

2included- R

2excluded)/(1 - R

2included) (Cohen,1988.; Kyu&

Sinkovics, 2013).The f2 analysis complements R

2 in the sense of examination of the effect sizes

of the impact of particular latent variables on the dependent latent variables. (Chin, 2010). We

used the f2 values of 0.02, 0.15 and0.35, respectively as guidelines for small, medium and large

effect sizes of the predictive variables (Cohen, 1988). Table 6presents a summary of respective

effect sizes of the main effect and the interaction effect variables at the structural level.

Table 6

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Effect size of the exogenous constructs:

DU Sample DEI Sample

GEB R2----------- 0.183 0.148

EBI R2----------- 0.21 0.25

ER R2----------- 0.19 0.14

f2

Path coefficient f

2

Path coefficient

ek-------- 0.1609 ek ->ebi 0.2462 0.1404 ek ->ebi 0.1053

er-------- 0.1268 er ->ebi 0.1900 0.1471 er ->ebi 0.2011

ebi------- 0.1601 ebi ->geb 0.4269 0.1819 ebi ->geb 0.3851

sec------ 0.8431 sec ->ebi 0.1026 0.1096 sec ->ebi 0.1909

sec ->er 0.1706 sec ->er 0.2281

* GEB =General Ecological Behaviour, ek =environmental knowledge, er =environmental responsibility,

ebi =environmental behavior intent, sec =spiritual ecological consciousness.

Post-hoc Analysis

Model estimation with data subset: As recommended by (Hair et al., 2012), we estimated our

conceptual framework on data subsets in order to test the stability of the estimates across

different smaller data sets and also on the compiled data. The PLS analysis results on the data

subsets are exhibited in the Table 6.The model estimates from the data subset are substantively

similar to those from the full data, although there are a few differences in size and / or level of

significance of values of some structural path coefficients. In summary, given the plausibly

high overall consistency between the model estimates obtained from the full data and the two

data subsets, it can be deduced that the PLS analysis results with full data are robust, and not

biased due to the nature of the sample included in the estimation procedure.

Analyzing heterogeneity through multi-group analysis. There can be a heterogeneity concern in

models that are analyzed by using PLS in the sense that different population parameters may be

distinctively at variance for subpopulations(Lew & Sinkovics, 2013). Therefore, with the

objective of examining the probable heterogeneity of the observations subject to various

eventualities, we carried out multi-group analysis in order to compare the two subpopulations

of Dayalbagh Educational Institute and Delhi University data using parametric approach.

(Table 7). As a result the standard errors of the structural paths between the groupings were

obtained by using bootstrapping procedure. Then the differences between the path coefficients

were tested using t-statistics. Subsequently, the path coefficients divergences were tested by

utilizing t- statistics.(Lew & Sinkovics, 2013).While there were differences between the path

coefficients of various constructs, however the t-test results clearly verified that except for a

few paths, these differences amidst the groups being studied are not significant, the reason

being that the students of DEI(54%) and DU (80%) have been exposed to value based

education system at school level.

Table 7

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Multi-group Chin test

Delhi University Data Dayalbagh Educational Institute

Data

Path

coefficient

standard

Error

t value Path

Coefficient

standard

Error

t value Test for

equality

of SE

ebi ->geb 0.4269 .1140 3.7429 .3851 .1092 3.5261 .0746

ek ->ebi 0.2462 .1034 2.4010 .3674 .1053 1.7982 .0409

er ->ebi .1900 .0956 1.9874 .2011 .0981 2.0499 .0517

geb -

>cpw

.6397 .0946 6.7644 .6874 .1050 6.5489 .3179

geb -

>eau

.7606 .0691 11.007 .6321 .0807 7.8317 .6103

geb -> gr .8028 .0697 11.517 .6949 .0869 7.9960 .8940

geb -

>npa

.5343 .2987 1.8180 .7869 .3762 2.0910 .9099

sec ->ebi .1026 .0578 1.7750 .1909 .0686 2.7823 .6984

sec ->er .1706 .2281

*ebi =environmental behavior intent, geb=general ecological behavior, ek =environmental knowledge, , evu=ecological

vehicle use, cpw=conservation of power and water gr= garbage reduction, npa= nature protection activity,

sec =spiritual ecological consciousness, er =environmental responsibility

DISCUSSION

The space between environmental stance and the conduct of behaviour that is pro-ecological

is unbridged and poses a severe challenge. The literature on environmental psychology does

engagingly encompass the subjects of attitude and behaviour (Smythe & Brook,1980), notions

deduced from sphere of morality and ethics (Heberlein,1972; Thogersen,1996) or behaviour

based on altruism (Hopper & Nielson,1991;Stern et al.,1993; Hallin,1995), on pro-social

norms (Granzin & Olsen,1991; Van Liere&Dunlap,1978) yet these multiple perspectives often

fall short to incorporate contemplations that improves the conditions of others at one‟s own

expense i.e. of humanity and other forms of life on earth.

Spirituality fosters an empathetic view of nature and with every bit of spiritual growth we

become more harmonious with it and the resolve to conserve it strengthens. In addition, the

ability to adapt with each other for the attainment of universal good takes precedence over

individual well-being. Spiritual ecology has wide connotations that reverberate all through

Hindu scriptural writings. The ancient eastern philosophies have laid emphasis on living in

harmony with nature and on identifying oneself with the several components of the universe.

The extant literature review of the western philosophy also converges towards the same. The

reverence for nature is sermonized in all religions and the truism of simple and uncomplicated

living is entrenched.

Kaiser et al (1999) have projected the environmental-values, knowledge, and ecological

behaviour intent as the minimal common denominator of nearly all approaches to

environmental attitude. In the present study, firstly, we proposed that environmental mindset

requires to be broadened to include the higher dimension of spirituality in the education system

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to promote a responsible ecological behavior. The connect between spiritual ecological

consciousness leading to environmental responsibility as well as strengthening of behavioural

intent as an intermediating factor converting in to responsible ecological behavioural conduct in

both the data sets of Delhi University (DU)(sec ->er 0.1706, er ->ebi 0.1900, ebi ->geb 0.4269)

and Dayalbagh Educational Institute (DEI) (sec->er 0.2281, er ->ebi 0.2011, ebi ->geb

0.3851) (Table 6)have been established satisfying the four hypotheses stated in the conceptual

model as appearing in section II.

Secondly, the differences in the ecological conduct of subsamples taken from the two

knowledge systems do not appear distinctly different owing to following reasons:

a) Exposure to value based education system since school days in the DU sample is higher

(80%) as against DEI sample (54%). Spiritual education as an integral part of the

curriculum through community service is imparted religiously in DEI Majority (70%)

of our respondents in DEI were Ist and IInd year undergraduate students. If we were to

expect its impact to be translated into responsible ecological conduct in a short span of

one year to two years only we would be over ambitious.

b) This transformation in behavioural aspect can only be tracked through time series data

and is an inference drawn from intuitive analysis. This hypothesis is based on intuitive

understanding about behaviour of people who have reached higher levels of

consciousness. The model used in the present study is a slightly modified model used

in Kaiser‟s study (1999,2000)and the results so obtained are robust and R2 are not very

high. We feel that the model needs to also incorporate the difficulties faced in the

conduct of ecological behaviour also and this appears to be a limitation of the study.

CONCLUSION AND RECOMMENDATIONS

The strength of the path coefficients in the two data sets of Delhi University and Dayalbagh

Educational Institute are slightly different. Spiritual ecological consciousness level as a

determinant of Ecological Behavior Intent is stronger in the DEI data vis-a-vis DU data but the

effect is small in both the data sets. From the study a scope for future research on the same

subject can be seen since the difficulties encountered by the respondents in the conduct of

ecological behavior also needs to be incorporated to have a greater variance explained by the

model. Also it appears that the spiritual ecological awareness is present amongst the students

but the conversion/transformation of this awareness to consciousness level is required at deeper

level in both the student communities; and this might happen with age and with continuous

practice. The seed of spiritual ecological bent must be sown at an early age but for this to show

conclusive results in terms modified behaviour might take time and can be expected to depend

on the strength of the awareness level to actually transcend the difficulty level in conducting

ecological behavior. The ancient and modern insights can be melded to reach higher intensity

of social, intellectual and spiritual progression which was far beyond the reach of preceding

generations particularly owing to immense potential exposure and awareness that we are

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endowed with. The restoration of spiritual, social and economic links of individuals to nature

are the prerequisites for the preparedness to achieve these heights. With the powerful gift of

consciousness, we can set out a unique journey guided by collective consciousness that shapes

the course of social, material, and spiritual advancement reshaping our relationship with the

living earth. These values need to be nurtured in the coming generations with caution and

compassion since early age.

ACKNOWLEDGMENTS

The authors wish to acknowledge the Vice Chancellor, Prof Dinesh Singh and Chairperson of

Delhi University Research Council, Prof Malashri Lal for initiating the Innovation Project

scheme and granting this Innovation Project to the authors as Primary Investigators. The

authors also wish to acknowledge the support that they received from the Principal, Maharaja

Agrasen College, Director, Cluster Innovation Centre, and external mentor, Professor Pami

Dua while undertaking this research. Last but not the least, it is the enthusiasm and hard work

of the student investigators: Bharat, Prakshi, Sunidhi, Danish, Aklmash, Swati,Siddharth,

Radhika, Akshay and Shubham that made the field work and data collection possible. Finally,

the investigators are thankful to the Chairman, Advisory Committee on Education, DEI, Vice

President, SPHEEHA and Director, DEI, Dayalbagh, Agra for facilitating this research.

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